ECG signal power vector detection of ischemia or infarction

ABSTRACT

A method comprising sensing at least one cardiac signal representative of cardiac activity of a subject using an implantable medical device (IMD), calculating, from the cardiac signal, a first dominant vector corresponding to a direction and magnitude of maximum signal power of an ST-T first segment of a cardiac cycle and a second dominant vector corresponding to a direction and magnitude of maximum signal power of a P-QRS second segment of a cardiac cycle, measuring a change in the first dominant vector, measuring a change in the second dominant vector, and subtracting the change in the second dominant vector from the measured change in the first dominant vector to form a difference.

CLAIM OF PRIORITY

This application is a Divisional of U.S. application Ser. No.11/275,880, now U.S. Pat. No. 7,567,836, filed Jan. 30, 2006, which isincorporated herein by reference in its entirety.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is related to the following, commonly assigned U.S.patent application Ser. No. 11/124,950, now U.S. Pat. No. 7,805,185,entitled “POSTURE MONITORING USING CARDIAC ACTIVATION SEQUENCES,” filedon May 9, 2005, and U.S. Provisional Patent Application Ser. No.60/631,742 entitled “CARDIAC ACTIVATION SEQUENCE MONITORING FOR ISCHEMIADETECTION,” filed on Nov. 30, 2004, each of which is hereby incorporatedby reference.

TECHNICAL FIELD

The field generally relates to implantable medical devices and, inparticular, but not by way of limitation, to systems and methods formonitoring electrical activity of the heart.

BACKGROUND

Implantable medical devices (IMDs) are devices designed to be implantedinto a patient. Some examples of these devices include cardiac functionmanagement (CFM) devices such as implantable pacemakers, implantablecardioverter defibrillators (ICDs), cardiac resynchronization devices,and devices that include a combination of such capabilities. The devicesare typically used to treat patients using electrical or other therapyand to aid a physician or caregiver in patient diagnosis throughinternal monitoring of a patient's condition. The devices may includeone or more electrodes in communication with sense amplifiers to monitorelectrical heart activity within a patient, and often include one ormore sensors to monitor one or more other internal patient parameters.Other examples of implantable medical devices include implantablediagnostic devices, implantable insulin pumps, devices implanted toadminister drugs to a patient, or implantable devices with neuralstimulation capability.

Additionally, some IMDs detect events by monitoring electrical heartactivity signals. In CFM devices, these events include heart chamberexpansions or contractions. Ischemia occurs when not enough bloodreaches the tissue of the heart. Detecting ischemia early is critical tothe health of the patient. Because of the damaged tissue, heartdepolarization becomes altered and an ischemic episode may be manifestedin the electrical signals.

SUMMARY

This document discusses, among other things, systems and methods formonitoring electrical activity of the heart. A system example includes aprocessor that in turn includes a cardiac signal vector module and anischemia detection module. The cardiac signal vector module isconfigured to measure a first dominant vector corresponding to adirection and magnitude of maximum signal power of a first segment of atleast one cardiac cycle of a subject and at least a second dominantvector corresponding to a direction and magnitude of maximum signalpower of a second segment of the cardiac cycle from an electricalcardiac signal. The ischemia detection module is configured to measure achange in the first dominant vector, to form a difference by subtractinga measured change in the second dominant vector from the measurement ofthe change in the first dominant vector, and to declare whether anischemic event occurred using the difference.

A method embodiment includes sensing at least one cardiac signalrepresentative of cardiac activity of a subject using an implantablemedical device (IMD), calculating a first dominant vector correspondingto a direction and magnitude of maximum signal power of a first segmentof a cardiac cycle and a second dominant vector corresponding to adirection and magnitude of maximum signal power of a second segment of acardiac cycle from the cardiac signal, measuring a change in the firstdominant vector, measuring a change in the second dominant vector, andsubtracting the change in the second dominant vector from the measuredchange in the first dominant signal vector to form a difference.

This summary is intended to provide an overview of the subject matter ofthe present patent application. It is not intended to provide anexclusive or exhaustive explanation of the invention. The detaileddescription is included to provide further information about the subjectmatter of the present patent application.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B illustrate an ECG waveform.

FIG. 2 illustrates referencing used to describe cardiac signal vectorsassociated with a depolarization wavefront.

FIG. 3A illustrates a polar plot of separate portions of a cardiac cyclethat may make up the cardiac vector.

FIG. 3B illustrates polar plots of cardiac vectors obtained fromselected portions of an electrocardiogram.

FIG. 4 is a graph of temporal profiles of a measure of a cardiac vector.

FIGS. 5A through 5D illustrate cardiac vectors superimposed over asectional view of the ventricles of a patient's heart.

FIG. 5E is a graph illustrating activation sequence vector angles for anST-T segment of a cardiac signal.

FIGS. 6A and 6B are block diagrams of a method of detecting a change inone or more cardiac signal vectors associated with all or a portion ofone or more cardiac activation sequences based on a source separation.

FIG. 7 illustrates ECG signal waveforms.

FIG. 8 is a block diagram of an example of a method of rejecting noisein cardiac activity measurements.

FIG. 9 shows a flow chart of an example implementation of a method toseparate posture noise from an ischemia measurement.

FIG. 10 is a block diagram of a system to implement a source signalseparation measurement.

FIG. 11 is an illustration of portions of an MD coupled by a lead orleads to a heart.

FIGS. 12A and 12B show an example of an IMD that does not useintravascular leads to sense cardiac signals.

FIG. 13 is a block diagram of portions of an example of an IMD.

FIG. 14 illustrates portions of a system that includes an IMD coupled toa heart of a subject.

FIG. 15 shows a block diagram of medical devices in communication withan advanced patient management (APM) system.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings which form a part hereof, and specific embodimentsin which the invention may be practiced are shown by way ofillustration. It is to be understood that other embodiments may be usedand structural or logical changes may be made without departing from thescope of the present invention.

The functions or algorithms described herein are typically implementedin software or a combination of software and human implementedprocedures in one embodiment. The software typically comprises computerexecutable instructions stored on computer readable media such as memoryor other type of storage devices. The term “computer readable media” isalso used to represent carrier waves on which the software istransmitted. Further, such functions typically correspond to modules,which are software, hardware, firmware or any combination thereof.Multiple functions are performed in one or more modules as desired, andthe embodiments described are merely examples. The software is typicallyexecuted on a digital signal processor, application specific integratedcircuit (ASIC), microprocessor, or other type of processor. Theprocessor may operate as part of an implantable medical device or theprocessor may operate on a computer system, such as a personal computer,server or other computer system.

An implantable medical device may include one or more of the features,structures, methods, or combinations thereof described herein. Forexample, a cardiac monitor or a cardiac stimulator may be implemented toinclude one or more of the advantageous features and/or processesdescribed below. It is intended that such a monitor, stimulator, orother implantable or partially implantable device need not include allof the features described herein, but may be implemented to includeselected features that provide for unique structures and/orfunctionality. Such a device may be implemented to provide a variety oftherapeutic or diagnostic functions.

A wide variety of implantable cardiac monitoring and/or stimulationdevices may be configured to implement a cardiac activation sequencemonitoring and/or tracking methodology. A non-limiting, representativelist of such devices includes cardiac monitors, pacemakers,cardiovertors, defibrillators, resynchronizers, and other cardiacmonitoring and therapy delivery devices, including cardiac devices thatinclude or work in coordination with neuro-stimulating devices, drugpumps, or other therapies. These devices may be configured with avariety of electrode arrangements, including transvenous, endocardial,and epicardial electrodes (i.e., intrathoracic electrodes), and/orsubcutaneous, non-intrathoracic electrodes, including can, header, andindifferent electrodes, and subcutaneous array or lead electrodes (i.e.,non-intrathoracic electrodes). Monitoring of electrical signals relatedto cardiac activity may provide early, if not immediate, diagnosis ofischemia. The present inventors have recognized a need for improvedsensing of events related to cardiac activity.

Method and system examples described herein reject noise in cardiacsignal separation methodologies. Signal separation methodologiesseparate composite signals into signals from individual sources.Composite cardiac signals typically are sensed using multipleimplantable electrodes. Signal separation is used to produce one or morecardiac activation signal vectors associated with one or more cardiacactivation sequences. A change in the signal vector may be detectedusing subsequent separations. The change may be used to diagnose,detect, predict, quantify, and/or qualify an event such as ischemia, anarrhythmia, a myocardial infarction, or other pathologic change.Information associated with the vectors may be stored and used to trackthe vectors. As an illustrative example, one component of noise in suchmeasurements is noise due to postural changes of a patient or subject.Rejecting the noise due to posture changes of a patient may improvespecificity of ischemic detection by reducing false positives.

The examples may be implemented in the context of a wide variety ofcardiac devices, such as those listed above, and are referred to hereingenerally as implantable medical devices (IMD) for convenience. An IMDmay incorporate one or more of the electrode types identified aboveand/or combinations thereof.

Cardiac activation sequence monitoring and/or tracking systems mayemploy more than two electrodes of varying location, and possibly ofvarying configuration. In one embodiment, for example, two or moreelectrodes may conveniently be located on the IMD header, whereas thehermetically sealed canister or “can” of the IMD itself may be the thirdelectrode. In another embodiment, one electrode may be located on theIMD header, another is the can electrode, and a third may be an IMDantenna used for radio frequency (RF) telemetry.

Electrocardiogram (ECG) signals originate from electrophysiologicalsignals originating in and propagated through the cardiac tissue, whichprovide for the cardiac muscle contraction that pumps blood through thebody. A sensed ECG signal is effectively a superposition of all thedepolarizations occurring within the heart that are associated withcardiac contraction, along with noise components. The propagation of thedepolarizations through the heart may be referred to as a depolarizationwavefront. The sequence of depolarization wavefront propagation throughthe chambers of the heart, providing the sequential timing of theheart's pumping, is designated an activation sequence.

ECG signals are sensed using one or more ECG sensing circuits. Examplesof ECG sensing circuits include surface ECG circuits, subcutaneous ECGcircuits, intracardiac electrogram (EGM) sensing circuits, and wirelessECG circuits. In a surface ECG sensing circuit, electrodes are placed ona subject's skin. In a subcutaneous ECG sensing circuit, electrodes areimplanted just beneath the skin and the ECG signal obtained is referredto as subcutaneous ECG or far-field electrogram. In an intracardiac EGMcircuit and in a wireless ECG circuit, at least one electrode is placedin or around the heart. A wireless ECG includes a plurality ofelectrodes to provide differential sensing of cardiac signals toapproximate a surface ECG. Descriptions of wireless ECG systems arefound in commonly assigned, co-pending U.S. patent application Ser. No.10/795,126 by McCabe et al., entitled “Wireless ECG in ImplantableDevices,” filed on Mar. 5, 2004, which is incorporated herein byreference.

A signal separation technique may be implemented to separate activationsequence components of ECG signals, and to produce one or more cardiacsignal vectors associated with all or a portion of one or more cardiacactivation sequences based on the separation. The activation sequencecomponents may be viewed as the signal sources that make up the ECGsignals, and the signal separation process may be referred to as asource separation process or simply source separation. One illustrativesignal source separation methodology useful for producing cardiac signalvectors associated with cardiac activation sequences is designated blindsource separation, which will be described in further detail below.

In general, the quality of the electrocardiogram or electrogram sensedfrom one pair of electrodes of an IMD depends on the orientation of theelectrodes with respect to the depolarization wavefront produced by theheart. The signal sensed on an electrode bipole is the projection of theECG vector in the direction of the bipole. Cardiac activation sequencemonitoring and/or tracking algorithms described herein advantageouslyexploit the strong correlation of signals from a common origin (theheart) across spatially distributed electrodes, such as to detect,monitor, and/or track the activation sequence for posture monitoring.

Referring to FIGS. 1A and 1B, an ECG waveform 100 describes theactivation sequence of a patient's heart as recorded, for example, by abipolar cardiac sensing electrode. The graph of FIG. 1A illustrates anexample of the ECG waveform 100 for three heartbeats, denoted as a firstheartbeat 110, a second heartbeat 120, and a third heartbeat 130. FIG.1B is a magnified view of the first two heartbeats 110, 120 of the ECGwaveform identified by bracket 1B in FIG. 1A.

Referring to the first heartbeat 110, the portion of the ECG waveformrepresenting depolarization of the atrial muscle fibers is referred toas a P-wave 112. Depolarization of the ventricular muscle fibers iscollectively represented by a Q 114, R 116, and S 118 waves of the ECGwaveform 100, typically referred to as the QRS complex, which is awell-known morphologic feature of electrocardiograms. Finally, theportion of the waveform representing repolarization of the ventricularmuscle fibers is known as a T wave 119. Between contractions, the ECGwaveform returns to an isopotential level. The segment of the cardiaccycle that includes the P-wave and extends to the S-wave is sometimesreferred to as the P-QRS segment, and the segment that begins at theonset of the S-wave and includes the T-wave is referred to as the ST-Tsegment.

The sensed ECG waveform 100 illustrated in FIGS. 1A and 1B is typical ofa far-field ECG signal, effectively a superposition of all thedepolarizations occurring within the heart that result in contraction.The ECG waveform 100 may also be obtained indirectly, such as by using asignal separation methodology. Signal separation methodologies, such asblind source separation (BSS), are able to separate signals fromindividual sources that are mixed together into a composite signal.Signal separation works on the premise that spatially distributedelectrodes collect components of a signal from a common origin (e.g.,the heart) with the result that these components may be stronglycorrelated to each other. In addition, these components may also beweakly correlated to components of another origin (e.g., noise). Asignal separation algorithm may be implemented to separate thesecomponents according to their sources and to produce one or more cardiacsignal vectors associated with all or a portion of one or more cardiacactivation sequences based on the source separation.

FIG. 2 illustrates a convenient reference for describing cardiac signalvectors associated with a depolarization wavefront. FIG. 2 is a polarplot 200 of a cardiac vector 240 superimposed over a frontal view of athorax 220, with the origin of the polar plot located at a patient'sheart 250, specifically, the atrioventricular (AV) node of the heart250. The heart 250 is a four-chambered pump that is largely composed ofa special type of striated muscle, called myocardium. Two major pumpsoperate in the heart, and they are a right ventricle 260, which pumpsblood into pulmonary circulation, and a left ventricle 270, which pumpsblood into the systemic circulation. Each of these pumps is connected toits associated atrium, called a right atrium 265 and a left atrium 275.

The cardiac vector 240 is describable as having an angle, in degrees,about a circle of the polar plot 200, and having a magnitude,illustrated as a distance from the origin of the tip of the cardiacvector 240. The polar plot 200 is divided into halves by a horizontalline indicating 0 degrees on the patient's left, and +/−180 degrees onthe patient's right, and further divided into quadrants by a verticalline indicated by −90 degrees at the patient's head and +90 degrees onthe bottom. The cardiac vector 240 is projectable onto thetwo-dimensional plane designated by the polar plot 200.

The cardiac vector 240 is a measure of all or a portion of theprojection of a heart's activation sequence onto the polar plot 200. Theheart possesses a specialized conduction system that ensures, undernormal conditions, that the overall timing of ventricular and atrialpumping produces adequate cardiac output, the amount of blood pumped bythe heart per minute. As described earlier, the normal intrinsicpacemaker of the heart is a self-firing unit located in the right atriumcalled the sinoatrial node. The electrical depolarization generated bythis structure activates contraction of the two atria. Thedepolarization wavefront then reaches the specialized conduction systemusing conducting pathways within and between the atria. Thedepolarization is conducted to the atrioventricular node, andtransmitted down a rapid conduction system composed of the right andleft bundle branches, to stimulate contraction of the two ventricles.

The normal pacemaker and rapid conduction system are influenced byintrinsic autonomic activity and by the autonomic nervous system, whichmodulates heart rate and the speed with which electrical depolarizationsare conducted through the specialized conduction system. There are manydiseases that interfere with the specialized conduction system of theheart, and many result in abnormally fast, slow, or irregular heartrhythms.

The cardiac vector 240 may be, for example, associated with the entirecardiac cycle, and may describe the mean magnitude and mean angle of thecardiac cycle. Referring now to FIG. 3A, a polar plot 300 is illustratedof separate portions of the cardiac cycle that may make up the cardiacvector 240 of FIG. 2. As is illustrated in FIG. 3A, a QRS vector 310 anda P vector 320 are illustrated having approximately 60 degree and 30degree angles, respectively. The QRS vector 310 may also be referred toas the QRS axis, and changes in the direction of the QRS vector may bereferred to as QRS axis deviations.

The QRS vector 310 represents the projection of the mean magnitude andangle of the depolarization wavefront during the QRS portion of thecardiac cycle onto the polar plot 300. The P vector 320 represents theprojection of the mean magnitude and angle of the depolarizationwavefront during the P portion of the cardiac cycle onto the polar plot300. The projection of any portion of the depolarization wavefront maybe represented as a vector on the polar plot 300.

Further, any number of cardiac cycles may be combined to provide astatistical sample that may be represented by a vector as a projectiononto the polar plot 300. Likewise, portions of the cardiac cycle overmultiple cardiac cycles may also be combined, such as combining aweighted summation of only the P portion of the cardiac cycle overmultiple cardiac cycles, for example.

Referring now to FIGS. 1A through 3A, the first, second, and thirdcardiac cycles 110, 120, and 130 may be analyzed using a window 140(FIG. 1A) applied concurrently to signals sensed by three or morecardiac sense electrodes. The ECG waveform signals 100 from all thesense electrodes, during the window 140, may be provided to a signalprocessor. The signal processor may then perform a source separationthat provides the cardiac vector 240 (FIG. 2). The cardiac vector 240then represents the orientation and magnitude of the cardiac vector thatis effectively an average over all three cardiac cycles 110, 120, and130.

Other windows are also useful. For example, a window 150 and a window160 may each provide a full cardiac cycle, such as the cardiac cycle 120and the cardiac cycle 130 illustrated in FIG. 1A, to a controller orprocessor for analysis. The windows 150, 160 may be useful forbeat-to-beat analysis, where the angle, magnitude, or other usefulparameter from the separated cardiac vector 240 is compared betweenconsecutive beats, or trended, for example.

Examples of other useful windows include a P-window 152, a QRS window154, and an ST window 155 (FIG. 1A) that provide within-beat vectoranalysis capability, such as by providing the P-vector 320 and theQRS-vector 310 illustrated in FIG. 3A. Providing a P-window 162 and/or aQRS-window 164, and/or an ST window 165 to subsequent beats, such as tothe consecutive cardiac cycle 130 illustrated in FIG. 1, provides forsubsequent separations that may provide information for tracking andmonitoring changes and/or trends of windowed portions of the cardiaccycle or statistical samples of P, QRS, or T waves over more than 1beat.

Referring now to FIG. 3B, polar plots of cardiac vectors obtained fromselected portions of an electrocardiogram are illustrated. In general,it may be desirable to define one or more detection windows associatedwith particular segments of a given patient's cardiac cycle. Thedetection windows may be associated with cardiac signal features, suchas P, QRS, ST, and T wave features, for example. The detection windowsmay also be associated with other portions of the cardiac cycle thatchange in character as a result of changes in the pathology of apatient's heart. Such detection windows may be defined as fixed ortriggerable windows.

Detection windows may include unit step functions to initiate andterminate the window, or may be tapered or otherwise initiate andterminate using smoothing functions such as Bartlett, Bessel,Butterworth, Hanning, Hamming, Chebyshev, Welch, or other functionsand/or filters. The detection windows associated with particular cardiacsignal features or segments may have widths sufficient to sense cardiacvectors resulting from normal or expected cardiac activity. Aberrant orunexpected cardiac activity may result in the failure of a given cardiacvector to fall within a range indicative of normal cardiac behavior.Detection of a given cardiac vector beyond a normal range may triggerone or more operations, including increased monitoring or diagnosticoperations, therapy delivery, patient or physician alerting,communication of warning and/or device/physiological data to an externalsystem (e.g., advanced patient management system) or other responsiveoperation.

An ECG signal 305 is plotted in FIG. 3B as signal amplitude 350 on theordinate versus time on the abscissa. One cardiac cycle is illustrated.The P portion of the ECG signal 305 may be defined using a P-window 335that opens at a time 336 and closes at a time 337. A source separationperformed on the ECG signal 305 within the P-window 335 produces the Pvector 320 illustrated on a polar plot 330. The angle of the P vector320 indicates the angle of the vector summation of the depolarizationwavefront during the time of the P-window 335 for the ECG signal 305.

The ST portion of the ECG signal 305 may be defined using an ST-window345 that opens at a time 346 and closes at a time 347. A sourceseparation performed on the ECG signal 305 within the ST-window 345produces the ST vector 350 illustrated on a polar plot 340. The angle ofthe ST vector 350 indicates the angle of the vector summation of therepolarization wavefront during the time of the ST-window 345 for theECG signal 305.

The P vector 320 and the ST vector 350 may be acquired as baselines, forfuture comparisons. If baselines for the P vector 320 and the ST vector350 are already established, the P vector 320 and ST vector 350 may becompared relative to their baselines for monitoring and trackingpurposes. As indicated above, detection of P vector 320 or ST vector 350beyond a predetermined range may trigger one or more responsiveoperations.

Cardiac activation sequence monitoring and tracking, to monitor changesand/or trends as described above, may be useful to determine initialactivation sequences, and track acute and chronic changes in theactivation sequences. Information from the patient's activation sequenceis valuable for identification, discrimination, and trending ofconditions such as conduction anomalies (e.g. AV block, bundle branchblock, retrograde conduction) and cardiac arrhythmias (e.g.discriminating between supraventricular tachycardia versus ventriculartachycardia, reentrant supraventricular tachycardia versus atrialfibrillation, or other desirable discrimination.) In addition tobaseline establishment, monitoring, and tracking, activation sequenceinformation may also be useful for determining pace capture forautocapture/autothreshold algorithms, adjustment, optimization, orinitiation of cardiac resynchronization therapy, and optimization orinitiation of anti-arrhythmia therapies, for example.

FIG. 4 illustrates another convenient reference for describing cardiacsignal vectors associated with a depolarization wavefront. FIG. 4 is agraph 400 of temporal profiles of a measure of a cardiac vector usefulfor diagnosing diseases and anomalous conditions in accordance with thesystem and methods described. The graph 400 contains a first temporalprofile 430 of a cardiac vector, and a second temporal profile 440 ofthe same cardiac vector after a change has occurred. An abscissa 420 ofthe graph 400 is time related, and an ordinate 410 of the graph 400 isrelated to a measure of the cardiac vector.

The ordinate 410 may be, for example, the angle of the cardiac vector. Anon-limiting, non-exhaustive list of measures of a vector useful for theordinate 410 includes: angle; magnitude; variance; power spectraldensity; rate of change of angle; rate of change of magnitude; rate ofchange of variance; or other measure indicative of a change in thecardiac activation sequence. As an example, consider the angle of the Pvector 320 illustrated in FIG. 3A. In this example, the ordinate 410would be indicated in degrees, with the first temporal profile 430varying from around 30 degrees. The abscissa 420 may be time, designatedin cardiac cycles, with a measure made of the P vector 320 for everycardiac cycle. The angle of the P vector 320 may be plotted on the graph400 at any interval of cardiac cycles, thereby displaying variance andtrends in the angle of the P vector 320 over many cardiac cycles.

After some change occurs, such as a pathological change in the patient'sheart, the second temporal profile 440 may be plotted using cardiaccycles occurring after the change. As is evident in the second temporalprofile 440 versus the first temporal profile 430, the variance of thesecond temporal profile 440 is significantly larger than the variance ofthe first temporal profile 430. Changes such as this may be detected andused to diagnose, verify and/or monitor diseases and/or cardiacconditions.

FIGS. 5A through 5D illustrate cardiac vectors superimposed over asectional view of the ventricles of a patient's heart 500. Referring toFIG. 5A, the ventricular portion of a patient's heart is illustratedhaving a right ventricle 510 and a left ventricle 520 separated by theheart's septum. The specialized conduction system includes anatrioventricular node 550, which is used as the origin for cardiacvectors, such as a mean QRS vector 525.

A right bundle branch 530 conducts the depolarization wavefront from theatrioventricular node 550 to the wall of the right ventricle 510.Illustrated in the wall of the right ventricle 510 are a series ofvectors 511-517, indicating the magnitude and angle of a local portionof the depolarization wavefront as it travels along the right ventricle510.

A left bundle branch 540 conducts the depolarization wavefront from theatrioventricular node 550 to the wall of the left ventricle 520.Illustrated in the wall of the left ventricle 510 are a series ofvectors 501-507, indicating the magnitude and angle of a local portionof the depolarization wavefront as it travels along the left ventricle520.

The mean QRS vector 525 is the vector summation of the vectors 511-517and the vectors 501-507. The mean QRS vector 525 may be typical of ahealthy heart, here illustrated at about 40 degrees angle if using thepolar plot of FIG. 3A. The mean QRS vector 525 varies from patient topatient depending on, for example, patient posture, and normalanatomical variation.

Referring now to FIG. 5B, the wall of the left ventricle 520 isenlarged, or hypertrophied, relative to FIG. 5A. In FIG. 5B, a dottedline 560 represents the wall of the left ventricle 520 in FIG. 5A,before hypertrophy. A series of local vectors 561-567 illustrate thelarger local contribution to the mean QRS vector 525 from thehypertrophy related vectors 561-567 relative to the normal series ofleft ventricle vectors 501-507.

FIG. 5C illustrates how the mean QRS vector 525 from a normal heart maychange to a mean hypertrophied QRS vector 565 after hypertrophy hasoccurred. For example, an IMD may be implanted in a patient, and aninitial analysis provides a baseline mean QRS vector 525 for thepatient, indicative of a normal condition of the left ventricle 520.After a period of time, the patient's heart may be subject tohypertrophy. An analysis performed post-hypertrophy may result infinding the mean hypertrophied QRS vector 565. This change may be usedto diagnose, verify and/or monitor hypertrophy of the patient's leftventricle.

Another example of a pathological change that may be diagnosed and/orverified using source separation is myocardial infarction. The sectionalview in FIG. 5D illustrates the left ventricle 520 having an infarctedportion 570 of the ventricular wall. The measurements were developedfrom a surface ECG. As is evident in the infarcted portion 570, nodepolarization is occurring, so only local depolarization vectors571-574 contribute to the mean cardiac vector from the left ventricle520. The infarction results in a change, for example, of the detectedmean QRS vector 525 to an infarcted mean QRS vector 580. Alternatively,the ST vector or the ST-T vector may show the change. This change isevident as the angle of the cardiac vector moves from the secondquadrant before infarction, to the third quadrant after infarction. Thelocation and extent of the infarction impacts the direction andmagnitude of the shift in the vector or vectors.

FIG. 5E is a graph 590 illustrating activation sequence ST-T vectorangles for the ST-T segment of a cardiac signal. The measurements weredeveloped from a live porcine subject using a wireless ECG system. Adominant vector of multiple individual activation sequence vectors iscomputed from multiple subcutaneous ECGs when monitoring and/or trackingcardiac activation sequence information. A baseline vector 592 for thedominant ST-T vector is shown. The graph 590 shows a shift in thedominant vector of ST-T vectors from the baseline vector 592 atapproximately 155 degrees to a dominant vector corresponding to partialocclusion of the left anterior descending coronary artery 594 at about125 degrees, and to a dominant vector corresponding to completeocclusion of the left anterior descending coronary artery 596. An IMDthat detects a change such as is illustrated in FIG. 5E has thepotential to alert the patient and/or physician to a loss or lesseningof blood supply to a portion of the heart muscle before permanent damageoccurs. Such early ischemia detection may result in greatly reducedmorbidity from these kinds of events.

FIG. 6A is a block diagram of a method 600 of detecting a change in oneor more cardiac signal vectors associated with all or a portion of oneor more cardiac activation sequences based on a source separation. Abaseline is established 610, providing information that may be monitoredor tracked relative to a patient's electrophysiological signals. Thebaseline 610 may be established from an initial source separation thatprovides initial cardiac signal information as a baseline. Alternately,or additionally, the baseline 610 may be established by an IMDmanufacturer from clinical data, or a patient's baseline 610 may beestablished by a clinician before, during, or after an IMD implantprocedure. The baseline 610 may be established as a rolling average ofrecent patient information from prior source separations, for example.

Evaluation criteria are established 620 to provide an index forcomparison to the baseline 610. For example, the evaluation criteria 620may be any parameter or characteristic determinable or measurable fromthe patient's electrophysiology information. A non-exhaustive,non-limiting list of evaluation criteria 620 includes: an angle changeof one or more cardiac signal vectors; a magnitude change of one or morecardiac signal vectors; a variance change of one or more cardiac signalvectors; a power spectral density change of the angle of one or morecardiac signal vectors; a power spectral density change of the magnitudeof one or more cardiac signal vectors; a trajectory change of one ormore cardiac signal vectors; a temporal profile change of one or morecardiac signal vectors; a rate of change of angle of one or more cardiacsignal vectors; a rate of change of magnitude of one or more cardiacsignal vectors; a rate of change of variance of one or more cardiacsignal vectors; a rate of change of temporal profile of one or morecardiac signal vectors; a trend of the angle of one or more cardiacsignal vectors; a trend of the magnitude of one or more cardiac signalvectors; a trend of the variance of one or more cardiac signal vectors;and a trend of the temporal profile of one or more cardiac signalvectors.

For example, an initial source separation may be performed by an IMD ona patient post-implant. The separation may produce the baseline 610 ofthe patient's average full cardiac cycle, such as the cardiac vector 240illustrated in FIG. 2. The vector 240 may have a characteristic, such asthe angle, determined as +45 degrees. The evaluation criteria 620 maybe, for example, that the patient's average full cardiac cycle vector'sangle should be within +40 to +50 degrees.

A comparison 630 is performed to determine the latest patientinformation relative to the baseline 610. For example, the results of alatest source separation algorithm may provide the latest average fullcardiac cycle vector's angle for the patient. Continuing with the aboveexample, the comparison 630 may check the latest angle of the patient'saverage full cardiac cycle vector's angle against the +40 to +50 degreecriteria.

A decision 640 selects an outcome based on the comparison 630. If thecriteria is met, for example if the latest angle is within +40 to +50degrees as outlined above, then a pattern A 650 is considered to be thepatient's latest condition. For example, the pattern A 650 may bedefined as an insufficient change to require some sort of action by theIMD. If a criterion 620 is not met at decision 640, then a pattern Acomplement 660 condition is considered to be the patient's latestcondition. The pattern A complement 660 condition may be defined asrequiring some sort of action by the IMD, such as reporting thecondition, further evaluating the patient's cardiac rhythms, preparing adefibrillator for a shock, or other desired action.

FIG. 6B is a block diagram of another embodiment of a method 605 ofdetecting a change in one or more cardiac signal vectors associated withall or a portion of one or more cardiac activation sequences, when thecriteria for baseline shift includes two criteria. It is contemplatedthat any number of criteria may be used or combined in the systems andmethods described. The use of two criteria with reference to FIG. 6B isfor purposes of explanation as to how to extend the methods to multiplecriteria, and is not intended as a limiting example.

A baseline is established 612, providing information that may bemonitored or tracked from a patient's electrophysiological signals. Thebaseline 612 may be established from an initial source separation thatprovides initial cardiac signal information as a baseline. Alternately,or additionally, the baseline 612 may be established by an IMDmanufacturer from clinical data, or a patient's baseline 612 may beestablished by a clinician before, during, or after an IMD implantprocedure. The baseline 612 may be established as a rolling average ofrecent patient information from prior source separations, for example.

Evaluation criteria are established 622 to provide indices forcomparison to the baseline 612. For example, the evaluation criteria 622may be any parameters or characteristics determinable or measurable fromthe patient's electrophysiology information. A non-exhaustive,non-limiting list of evaluation criteria 622 includes those describedpreviously with respect to FIG. 6A. It is further contemplated that asingle criterion may be compared with respect to multiple baselines,and/or that multiple criteria may each be compared with respect to theirown unique baseline established for each particular criterion.

Baselines may be pre-defined using, for example, clinical data, and/orbaselines may be established using initial source separations. Forexample, and described in more detail below, a source separation mayprovide an orthogonal coordinate system; with vectors described using aseries of coefficients matched to a series of unit direction vectors.One or more angles may be calculated using trigonometric identities toindicate a vector's direction relative to other vectors in thecoordinate system. Subsequent source separations provide revised sets ofcoefficients, from which changes in vector direction may be determinedusing the same trigonometric identities. In an n-dimensional space,(n−1) angles may be resolved and used for comparison and tracking.

For example, an initial source separation may be performed by an IMD ona patient post-implant. The separation may produce the baseline 612 ofthe patient's cardiac cycle, such as the QRS-vector 310 and the P-vector320 illustrated in FIG. 3A. The QRS-vector 310 may have the angledetermined as +45 degrees. The P-vector 320 may have the angledetermined as +28 degrees. The evaluation criteria 622 may be, forexample, that the patient's QRS-vector's angle should be within +40 to+50 degrees and that the patient's P-vector angle should be within +25to +30 degrees.

A comparison 632 is performed to determine the latest patientinformation relative to the baseline 612. For example, the results of alatest source separation algorithm may provide the latest angles of theQRS-vector and P-vector for the patient. Continuing with the aboveexample, the comparison 632 may check the latest angles of the patient'sQRS-vector and P-vector against the +40 to +50 degree and +25 to +30degree criteria respectively.

A first decision 642 selects a first outcome based on the comparison632. If the first criteria is met, for example if the latest angle ofthe QRS-vector is within +40 to +50 degrees as outlined above, then apattern A 652 is considered to be the patient's latest condition. Forexample, the pattern A 652 may be defined as an insufficient change torequire some sort of action by the IMD. If a criterion 622 is not met atdecision 642, then a pattern A complement 662 condition is considered tobe the patient's latest condition. The pattern A complement 662condition may be defined as requiring some sort of action by the IMD,such as reporting the condition, further evaluating the patient'scardiac rhythms, preparing a defibrillator for a shock, or other desiredaction.

A second criteria decision 672 is performed to check for a secondoutcome based on the second criteria. If the second criteria is met, forexample if the latest angle of the P-vector is within +25 to +30 degreesas outlined above, then a pattern B 682 is considered to be thepatient's latest condition. For example, the pattern B 682 may bedefined as an insufficient change to require some sort of second actionby the IMD. If the criterion 622 is not met at decision 672, then apattern B complement 692 condition is considered to be the patient'slatest condition. The pattern B complement 692 condition may be definedas requiring some sort of second action by the IMD.

Table 1 below provides a non-limiting non-exhaustive list of conditionsthat may be detected by monitoring and/or tracking cardiac activationsequences in the systems and methods described.

TABLE 1 Conditions associated with QRS Axis Deviations First Source(Normal −30 to +90 degrees) Left Axis Deviation: ≧−30° Left AnteriorFascicular Block (LAFB) axis −45° to −90° Some cases of inferiormyocardial infarction with QR complex Inferior Myocardial Infarction +LAFB in same patient (QS or QRS complex) Some cases of left ventricularhypertrophy Some cases of left bundle branch block Ostium primum AtrialSeptal Defect and other endocardial cushion defects Some cases ofWolff-Parkinson-White syndrome syndrome (large negative delta wave )Right Axis Deviation: ≧+90° Left Posterior Fascicular Block (LPFB): Manycauses of right heart overload and pulmonary hypertension High lateralwall Myocardial Infarction with QR or QS complex Some cases of rightbundle branch block Some cases of Wolff-Parkinson-White syndromeChildren, teenagers, and some young adults Bizarre QRS axis: +150° to−90° Dextrocardia Some cases of complex congenital heart disease (e.g.,transposition) Some cases of ventricular tachycardia Second Source QRSAxis Deviation Left anterior fascicular block (LAFB) Right ventricularhypertrophy Left bundle branch block Acute Myocardial Infarction:Hypertensive heart disease Coronary artery disease Idiopathic conductingsystem disease Acute Myocardial Infarction- inferior left ventricularfree wall accessory pathway (Wolff-Parkinson-White syndrome)Posteroseptal accessory pathway left posterior fascicular block ChronicObstructive Pulmonary Disease (uncommon - 10%) Other conduction defects:left ventricular hypertrophy Right bundle branch block Elevateddiaphragm: R anterior hemiblock Pregnancy Pacing of R ventricleAbdominal mass Pulmonary conditions Ascites Pulmonary hypertension TumorChronic Obstructive Pulmonary Disease Conduction defects:Emphysema/bronchitis R ventricular (apical) pacing Pulmonaryemboli/infarcts Systemic hypertension, esp. chronic Congenital defectsValvular lesions Rheumatic heart disease Pulmonic stenosis Aorticregurgitation Mitral regurgitation Mitral stenosis Coarctation of theaorta Tricuspid regurgitation Hyperkalemia Pulmonic stenosis Normalvariant in obese and in elderly Pulmonic regurgitation

As discussed previously in regard to FIG. 5E, monitoring the ST-Tsegment by source separation is useful in detecting occlusion. However,posture changes of the patient may also cause a deviation in the STsegment of an ECG signal. This could lead to the source separationmeasurement process providing false indications of ischemia. Posturechanges affect the morphology of an ECG signal over the complete cardiaccycle while ischemia is most likely to mainly affect the ST-T wave. FIG.7 illustrates a baseline ECG signal waveform 700 and an ECG signalwaveform reflecting ischemia 710. The waveforms 700, 710 are separatedinto P-QRS segments 702, 712 and ST-T segments 704, 714. The changebetween the P-QRS segments 702, 712 is mostly due to any change inposture of the patient. The change between the ST-T segments 704, 714includes both a change due to any posture change and the change due toischemia.

FIG. 8 is a block diagram of an example of a method 800 of rejectingnoise in cardiac activity measurements. At 810, at least one cardiacsignal representative of cardiac activity of a subject is sensed usingan implantable medical device (IMD). At 820, a first dominant vectorcorresponding to a direction and magnitude of maximum signal power of afirst segment of a cardiac cycle and a second dominant vectorcorresponding to a direction and magnitude of maximum signal power of asecond segment of a cardiac cycle are calculated from the cardiacsignal. A dominant vector is calculated from a central tendency of thevector, such as a mean magnitude and direction of the vector forexample. In some examples, the first segment includes the ST-T segmentand the second segment includes the P-QRS segment, but other segments orcombination of segments can be used.

At 830, a change is measured in the first dominant vector. At 840, achange is measured in the second dominant vector. In some examples,measuring a change includes measuring a change in at least one of achange in the direction angle of a dominant vector and a change in themagnitude of a dominant vector. In some examples, measuring a changeincludes establishing a baseline vector, such as by computing a centraltendency of a dominant vector, and measuring a change from the baseline.In some examples, measuring a change includes trending at least onedominant vector, and detecting a change from the trending. If the changein the first dominant vector includes a measured change that is ofinterest as well as measured noise, and the second dominant vectorincludes mostly measured noise, then the measured change of interest isobtained by (at 850) subtracting the change in the second dominantvector from the measured change in the first dominant signal vector toform a difference. The difference includes the measured change that isof interest with the noise reduced.

As discussed previously, postures changes are a source of noise inischemia measurements. FIG. 9 shows a flow chart of an exampleimplementation of the more general method of FIG. 8 to separate posturenoise from the ischemia measurement. Referring to FIGS. 9 and 7, at 910,a baseline vector is computed for the baseline P-QRS segment 702(O_(PR)) and a baseline vector is computed for the baseline ST-T segment712 (O_(ST)). When an ischemic event or episode occurs, a shift in thedominant vector of the P-QRS segment (O_(PR)′) occurs and a change inthe dominant vector of the ST-T segment (O_(ST)′) occurs. At 920, theshift in the dominant vector O_(ST)′ is detected. The difference betweenthe post-ischemia dominant vector of the ST-T vector and the baselinevector (O_(ST)′−O_(ST)) reflects a measured shift due to both ischemiaand posture changes. This difference is measured at 930. At 940 it isdetermined whether the shift is greater than predetermined shiftthreshold. Predetermined refers to the threshold value being fixed or tothe threshold value being programmable.

At 950, the shift in the dominant vector O_(PR)′ is determined. Becauseany measured shift in the P-QRS segment would be mostly due to anychange in posture from the patient, the difference between thepost-ischemia dominant vector of the P-QRS vector and the dominantbaseline vector (O_(PR)′−O_(PR)) reflects a shift due to posturechanges. At 960, this difference is measured. To obtain the measuredshift due to ischemia without the posture change, the difference in thevectors of the P-QRS segment is subtracted from the difference in thevectors of the ST-T segments, i.e.Shift due to ischemia=(O _(ST) ′−O _(ST))−(O _(PR) ′−O _(PR)).  (1)At 970, the shift due to ischemia is compared to a predeterminedthreshold. The predetermined threshold in 970 may be the same thresholdvalue as in 940 or it may be a different threshold value. If the shiftdue to ischemia is greater than a threshold shift, then an ischemicevent may be declared, or preferably, the fact that such a shiftoccurred is combined with other ischemia detection criteria at 980.

In some examples, the measured shift in the ST segment is combined withthe measured output from one or more sensors, such as to measureintracardiac or trans-thoracic impedance, blood pressure. In someexamples, at least one rule is used to blend the outputs of the varioussensors to make a decision as to whether a patient has experienced anischemic event. In some examples, weights are assigned to correspondingoutputs of the sensors and the ST measurement, and at least one rule isapplied to merge the sensor outputs and the measured shift in the STsegment using the weights and determine whether an ischemic eventoccurred. In some examples, one or more fuzzy logic rules are appliedthat use the weights to merge the sensor outputs and the measured shiftin the ST segment to determine whether an ischemic event occurred.

In some examples, an ischemic event is not declared unless the thresholdis exceeded in X of Y consecutive cardiac cycles, where X is a positiveinteger less than positive integer Y. As an illustrative example, X iseight and Y is ten and an ischemic event is not declared unless thepredetermined threshold is exceeded in at least eight of ten cardiaccycles.

FIG. 10 is a block diagram of a system 1000 comprising a processor 1010that includes a cardiac signal vector module 1020 and an ischemiadetection module 1030. The cardiac signal vector module 1020 measures afirst dominant vector corresponding to a direction and magnitude ofmaximum signal power of a first segment of at least one cardiac cycle ofa subject and at least a second dominant vector corresponding to adirection and magnitude of maximum signal power of a second segment ofthe cardiac cycle from an electrical cardiac signal. The cardiac signalvector module 1020 measures a dominant vector by any of the methodsdescribed previously. The first and second segments can be any segmentsof the cardiac cycle such as the ST-T segment and the P-QRS segment.

The ischemia detection module 1030 measures a change in the firstdominant vector. In some examples, the cardiac signal vector module 1020computes a baseline vector for each of the dominant vectors and theischemia detection module 1030 measures a change in the first and seconddominant vector by measuring a change from the baselines. The ischemiadetection module 1030 forms a difference by subtracting a measuredchange in the second dominant vector from the measurement of the changein the first dominant vector. Whether an ischemic event occurred isdeclared using the difference using any of the methods describedpreviously.

In some examples, the processor 1010 is included in an implantablemedical device (IMD). Examples of an IMD include, without limitation, apacer, a defibrillator, a cardiac resynchronization therapy (CRT)device, or a combination of such devices. Other examples includeimplantable diagnostic devices, a drug pump, and a neural stimulationdevice.

FIG. 11 is an illustration of portions of an IMD 1100 coupled by a lead1108 or leads to a heart 1105. Lead 1108 includes one or more electrodes1110, 1112, 1114, and 1116. The electrodes include an electricalconnection to individual lead wires. The electrodes are separated byinsulating segments 1126. In the lead example shown, tip electrode 1110and ring electrode 1112 are for placement in the right ventricle, andring electrodes 1114 and 1116 are for placement in the right atrium. Theelectrodes provide for sensing signals, delivering pacing therapy, orboth sensing signals and delivering pacing therapy. Voltages are senseddifferentially, such as between electrodes 1110 and 1112 in theventricle and 1114 and 1116 in the atrium, or pacing energy is delivereddifferentially between the electrodes, or pacing and sensing areprovided differentially. In some examples, the electrodes include anelectrode 1118 formed on the IMD can 1120. In some examples, the entirecan 1120 is an electrode. In some examples, the electrodes include anelectrode 1122 formed on the IMD header 1124.

In some examples, electrodes 1110 and 1112 are provided on a first leadand electrode 1114 is a tip electrode and electrode 1116 is a ringelectrode provided on a second lead. In some examples, an additionallead that includes ring electrodes placed in a coronary vein lyingepicardially on the left ventricle via the coronary vein to providesensing and or pacing to the left ventricle.

Lead 1108 optionally also delivers atrial cardioversion, atrialdefibrillation, ventricular cardioversion, ventricular defibrillation,or combinations thereof to heart 1105 through the electrodes. Suchelectrodes typically have larger surface areas than pacing electrodes inorder to handle the larger energies involved in defibrillation. A leadoptionally provided in the left ventricle via the coronary vein providesresynchronization therapy to the heart 1105.

Other forms of electrodes include meshes and patches which may beapplied to portions of heart 1105 or which may be implanted in otherareas of the body to help “steer” electrical currents produced by IMD1100. The present methods and systems will work in a variety ofconfigurations and with a variety of electrodes. FIGS. 12A-B show anexample of an IMD 1200 that does not use intravascular leads to sensecardiac signals. FIG. 12A shows that the IMD 1200 includes a thicker end1213 to hold the power source and circuits. The IMD 1200 also includeselectrodes 1225 and 1227 for remote sensing of cardiac signals.Cardioversion/defibrillation is provided through electrodes 1215 and1217. FIG. 12B shows the positioning of the IMD 1200 within a patient.

FIG. 13 is a block diagram of portions of an example of an IMD 1300 thatincludes a processor 1305 that in turn includes a cardiac signal vectormodule 1310 and an ischemia detection module 1315. The processor 1305detects ischemia using any of the methods described herein. In someexamples, the processor 1305 is included in a controller circuit thatcontrols operation of the IMD 1300. Additionally, the IMD includesimplantable tip electrodes 1320, 1330 and implantable ring electrodes1325, 1335 provided on leads 1340 and 1345. The electrodes are adaptedfor spatial distribution within the subject. The leads in the exampleare bipolar leads for placement in an atrium or ventricle. Otherelectrode combinations are possible, such as additional lead electrodes,or can electrodes, or header electrodes.

The IMD 1300 also includes at least one cardiac signal sensing circuit1350 in communication with the electrodes. The cardiac signal sensingcircuit 1350 produces an electrical cardiac signal representative ofcardiac activity of the subject. The cardiac signal sensing circuit 1350senses electrical cardiac activity signals associated with an activationsequence of a heart. The activity signals propagate through the heart'selectrical conduction system to excite various regions of myocardialtissue. The sensing circuit 1350 provides an electrical signalrepresentative of such signals. Examples of cardiac signal sensingcircuits 1350 include, without limitation, a subcutaneous ECG sensingcircuit, an intracardiac electrogram (EGM) sensing circuit, and awireless ECG sensing circuit. The wireless ECG circuit includes aplurality of electrodes adapted for placement to sense a cardiac signalapproximating a surface ECG. The IMD 1300 includes a therapy circuit1355 to provide electrical pacing or defibrillation therapy. IMD 1300optionally includes a switch network 1360 to isolate the cardiac signalsensing circuit 1350 during therapy delivery.

In some examples, when the processor 1305 detects ischemia, theprocessor 1305 activates an alarm, such as a buzzer or other audibleindication in the IMD 1300, to indicate that an ischemic event occurred.

In some examples, the IMD 1300 includes one or more other sensors, suchas to measure intracardiac or trans-thoracic impedance, or bloodpressure. In some examples, the processor 1305 uses at least one rule toblend the outputs of the various sensors and at least one signalseparation measurement to make a decision as to whether a patient hasexperienced an ischemic event.

In some examples, the IMD 1300 includes a memory circuit 1365. Theprocessor 1305 calculates trend data of measured subsequent changes fromat least one baseline vector by any of the methods described herein andstores the trend data in the memory circuit 1365. In some examples, theprocessor 1305 establishes a value of the ischemia indication measuredusing the trend data and stores an ischemia indication using the trenddata. In some examples, the IMD 1300 includes a communication circuit1370 to communicate wirelessly with an external device. The indicationof the ischemic event or an alarm can then be transmitted to a caregiverusing the external device. The external device may receive an alarmstatus from the IMD 1300 when the IMD 1300 is next interrogated or by acommunication originating from the IMD 1300. The alarm may be used tonotify the patient, a caregiver, or both a patient and caregiver of theischemic event.

FIG. 14 illustrates portions of a system 1400 that includes an IMD 1420coupled to heart 1405 of a subject 1410 via a lead 1408. The system 1400further includes an external device 1425 that communicates wirelesssignals 1430 with the IMD 1420. In the system 1400, the external device1425 instead of the IMD 1420 includes a processor 1435 that in turnsincludes a cardiac signal vector module 1440 and an ischemia detectionmodule 1445. The IMD 1420 includes a plurality of implantable electrodesadapted for spatial distribution within the subject 1410, and at leastone cardiac signal sensing circuit in communication with the electrodes.The cardiac signal sensing circuit produces an electrical cardiac signalrepresentative of cardiac activity of the subject 1410. The IMD includesa controller circuit coupled to the cardiac signal sensing circuit tocontrol IMD functions and a communication circuit coupled to thecontroller circuit. The IMD 1420 communicates information related tocardiac electrical signals with the external device 1425 and theprocessor 1435 in the external device 1425 detects ischemia using any ofthe methods described herein.

In some examples, the external device 1425 includes a display. Thisallows a caregiver to read a signal sampled after an ischemic event outfrom device memory and observe the event at a subsequent patient visit.An indication in the IMD is communicated to an external device to alertthe caregiver of the event. Additionally, the external device 1425displays a graph such as the graph in FIG. 5E to indicate the change incomputed vectors. In some examples, an external device 1425 locatedsomewhere other than in a clinic, such as in a patient's home, can readout and communicate the sampled signal to the caregiver's location fordisplay. This monitoring identifies those patients that experienceischemia to a caregiver, allowing the caregiver to notify emergencypersonnel, or to make adjustments to parameters of a CFM device, or toadjust a patient's drug therapy.

Examples of the external device 1425 include an IMD programmer. In someexamples, the external device 1425 is part of, or in communication with,a computer network such as a hospital computer network or the internet.An indication of the ischemic event or an alarm can then be transmittedto a caregiver using the network. An indication or alarm provided to thepatient has further uses, such as to direct the patient to take a drug,adjust medication, or to seek immediate medical assistance. In someexamples, the external device 1425 is in communication with a mobiletelephone network. In some examples, the external device is a repeaterthat communicates wirelessly with the IMD 1420 and with a third devicein communication with a network, such as a computer network or mobiletelephone network.

FIG. 15 shows an example of medical devices that communicate with anadvanced patient management (APM) system 1500. An APM system is acommunication infrastructure that allows physicians and caregivers toremotely and automatically monitor, among other things, cardiac andrespiratory functions of patients. The APM system also allows for remoteand/or automatic adjusting of devices internal or external to a patientthat provide patient therapy. The APM system 1500 communicates witheither implantable medical devices 1505 or patient external medicaldevices 1510. Examples of a patient external device includes externalpatient monitoring and therapy delivery devices, including cardiacdevices that include or work in coordination with neuro-stimulatingdevices. In some examples, the communication is through medical deviceprogrammers 1515 that the APM communicates with over a network. An MDprogrammer 1515 communicates wirelessly with the IMD 1505. In someexamples, the APM system 1500 communicate directly with the medicaldevices 1505, 1510 through repeaters 1520 that communicate wirelesslywith the medical devices 1505, 1510 and the APM system 1500.

The processor of FIG. 10 can reside in the IMD 1505 or the externalmedical device 1510 or an IMD programmer 1515. FIG. 15 shows a processor1525 having a cardiac signal vector module 1530 and an ischemiadetection module 1535 included in an APM system server 1540. The IMD1505 communicates information related to cardiac electrical signals withan external device such as a repeater 1520 or an IMD programmer 1515.The information is relayed to the APM system server 1540 over a networksuch as a computer network or a wireless communication network. Theprocessor 1525 detects ischemia using any of the methods describedherein. In some examples, the server 1540 initiates at least onedominant vector measurement. The measurement may be automaticallytriggered periodically, such as by a client running on the server 1540,or it may be initiated through the server 1540 by a user such as aclinician.

Noise may cause deviation of the ST or ST-T segment of the cardiaccycle, which may lead to false detections of ischemia from ECG orelectrogams (EGM). One source of such is postural changes of a patient.The systems and methods described herein allow this noise to beattenuated or removed from measurements used to detect ischemia. Thiscould remove ECG morphological variations due to noise such as posturalchange thereby reducing false-positives in measurements and improvespecificity of ischemia detection. It is to be noted that the systemsand methods described herein are applicable to remove sources of noiseother than postural change noise and to remove noise from measurementsother than ischemia measurements. The systems and methods can be used inany measurement using a dominant vector where the measured event affectsa part of the cardiac cycle while the noise affects another part of thecardiac cycle or the entire cardiac cycle. A change in a first dominantvector will include a measured change that is of interest as well asmeasured noise. A change in a second dominant vector includes mostlyonly the measured noise. Forming a difference of the changes will resultin a measurement that mostly includes the measured change that is ofinterest.

The accompanying drawings that form a part hereof, show by way ofillustration, and not of limitation, specific embodiments in which thesubject matter may be practiced. The embodiments illustrated aredescribed in sufficient detail to enable those skilled in the art topractice the teachings disclosed herein. Other embodiments may beutilized and derived therefrom, such that structural and logicalsubstitutions and changes may be made without departing from the scopeof this disclosure. This Detailed Description, therefore, is not to betaken in a limiting sense, and the scope of various embodiments isdefined only by the appended claims, along with the full range ofequivalents to which such claims are entitled.

Such embodiments of the inventive subject matter may be referred toherein, individually and/or collectively, by the term “invention” merelyfor convenience and without intending to voluntarily limit the scope ofthis application to any single invention or inventive concept if morethan one is in fact disclosed. Thus, although specific embodiments havebeen illustrated and described herein, it should be appreciated that anyarrangement calculated to achieve the same purpose may be substitutedfor the specific embodiments shown. This disclosure is intended to coverany and all adaptations, or variations, or combinations of variousembodiments. Combinations of the above embodiments, and otherembodiments not specifically described herein, will be apparent to thoseof skill in the art upon reviewing the above description.

The Abstract of the Disclosure is provided to comply with 37 C.F.R.§1.72(b), requiring an abstract that will allow the reader to quicklyascertain the nature of the technical disclosure. It is submitted withthe understanding that it will not be used to interpret or limit thescope or meaning of the claims. In addition, in the foregoing DetailedDescription, it can be seen that various features are grouped togetherin a single embodiment for the purpose of streamlining the disclosure.This method of disclosure is not to be interpreted as reflecting anintention that the claimed embodiments require more features than areexpressly recited in each claim. Rather, as the following claimsreflect, inventive subject matter lies in less than all features of asingle disclosed embodiment. Thus the following claims are herebyincorporated into the Detailed Description, with each claim standing onits own.

1. A method comprising: sensing at least one cardiac signalrepresentative of cardiac activity of a subject using an implantablemedical device (IMD); calculating, from the cardiac signal, a firstdominant vector corresponding to a direction and magnitude of maximumsignal power of an ST-T first segment of a cardiac cycle and a seconddominant vector corresponding to a direction and magnitude of maximumsignal power of a P-QRS second segment of a cardiac cycle, wherein theP-QRS segment includes the P-wave and extends to and includes theS-wave; measuring a change in the first dominant vector; measuring achange in the second dominant vector; subtracting the change in thesecond dominant vector from the measured change in the first dominantvector to form a difference; and deeming an ischemic event to haveoccurred at least in part from whether the difference exceeds aspecified threshold value.
 2. The method of claim 1, further includingactivating an alarm indicative of the deemed ischemic event.
 3. Themethod of claim 1, wherein deeming an ischemic event to have occurredfurther includes deeming an ischemic event if the difference exceeds thespecified threshold value in X of Y consecutive cardiac cycles, whereinX and Y are integers and X is less than or equal to Y.
 4. The method ofclaim 1, comprising establishing a baseline vector for at least one ofthe first and second dominant vectors and measuring a change from thebaseline vector.
 5. The method of claim 4, wherein establishing abaseline vector includes calculating a central tendency for at least oneof the first and second dominant vectors.
 6. The method of claim 4,comprising reducing noise related to posture by subtracting the measuredchange in the second dominant vector from the measured change in thefirst dominant vector to form a difference.
 7. The method of claim 4,wherein measuring the change from the baseline vector includes:subtracting a first baseline vector from a later-measured first dominantvector to obtain a first change representative of a change due toposture during the first segment; subtracting a second baseline vectorfrom a later-measured second dominant vector to obtain a second changerepresentative of a change due to posture and ischemia during the secondsegment; and subtracting the first change from the second change toobtain a third change representative of a change due to ischemia.
 8. Themethod of claim 4, comprising measuring a trend in at least one of thefirst and second dominant vectors.
 9. The method of claim 8, includingstoring an ischemia indication using the measured trend.
 10. The methodof claim 1, wherein measuring a change in the first dominant vector andmeasuring a change in the second dominant vector comprises measuring atleast one of a change in angle, a change in magnitude, a variance of theangle or the magnitude, a power spectral density, a rate of change ofthe angle, a rate of change of the magnitude, and a rate of change ofthe variance of the angle or the magnitude.
 11. The method of claim 1,further including deeming an ischemic event to have occurred fromwhether the difference exceeds a specified threshold value incombination with a measured output from one or more sensors.
 12. Themethod of claim 11, wherein deeming an ischemic event to have occurredincludes blending the output of at least one sensor and the differenceaccording to at least one rule.
 13. The method of claim 1, whereinsensing a cardiac signal includes sensing a cardiac signal approximatinga surface electrocardiogram (ECG).
 14. A system comprising animplantable medical device (IMD) comprising: a plurality of implantableelectrodes adapted for spatial distribution within a subject; and atleast one cardiac signal sensing circuit in communication with theelectrodes, the cardiac signal sensing circuit operable to produce anelectrical cardiac signal representative of cardiac activity of thesubject; and means for calculating, from the electrical cardiac signal,a first dominant vector corresponding to a direction and magnitude ofmaximum signal power of an ST-T first segment of at least one cardiaccycle of the subject and at least a second dominant vector correspondingto a direction and magnitude of maximum signal power of a P-QRS secondsegment of the cardiac cycle, wherein the P-QRS segment includes theP-wave and extends to and includes the S-wave, and forming a differenceby subtracting a measured change in the second dominant vector from ameasured change in the first dominant vector, and using the differenceto reduce noise in the measured change in the first dominant vector. 15.The system of claim 14, further including means to create trend data ofchanges in at least one dominant vector.
 16. The system of claim 14,further including means for communicating the trend data to a networkserver system.
 17. The system of claim 14, wherein the means forcalculating is further configured to: establish first and secondbaseline vectors for the first and second dominant vectors; and measurea change in a dominant vector relative to a baseline vector.
 18. Thesystem of claim 17, wherein the means for calculating is furtherconfigured to: subtract the first baseline vector from a later-measuredfirst dominant vector to obtain a first change representative of achange due to posture during the first segment; subtract the secondbaseline vector from a later-measured second dominant vector to obtain asecond change representative of a change due to posture and ischemiaduring the second segment; and subtract the first change from the secondchange to obtain a third change representative of a change due toischemia.
 19. The system of claim 17, wherein the wherein the means forcalculating is further configured to measure a change in a dominantvector by measuring at least one of a change in angle, a change inmagnitude, a variance of the angle or the magnitude, a power spectraldensity, a rate of change of the angle, a rate of change of themagnitude, and a rate of change of the variance of the angle or themagnitude.